JMIR Publications

ABSTRACT

Background:

In the era of big data, the intensive care unit (ICU) is very likely to benefit from real-time computer analysis and modeling based on close patient monitoring and Electronic Health Record data. MIMIC is the first open access database in the ICU domain. Many studies have shown that common data models (CDMs) improve database searching by allowing code, tools and experience to be shared. OMOP-CDM is spreading all over the world.

Objective:

The objective was to to transform MIMIC into an OMOP database, and to evaluate the benefits of this transformation for analysts.

Methods:

We transformed MIMIC (version 1.4.21) in the OMOP format (5.3.3.1), through a semantic and structural mapping. The structural mapping aimed at moving the MIMIC data into the right place in OMOP with some data transformations. It parted into three phases: conception, implementation and evaluation. The conceptual mapping aimed at aligning the MIMIC local terminologies to the OMOP's standard ones. It consisted of three phases: integration, alignment and evaluation. A documented, tested, versioned, exemplified and open repository has been set up to support the transformation and improvement of the MIMIC community's source code. The resulting data set was evaluated over a 48-hour datathon.

Results:

With an investment of 2 people for 500 hours, 64% of the data items of the 26 MIMIC tables have been standardized into the OMOP CDM and 78% of the source concepts mapped to reference terminologies. The model proved its ability to support community contributions and was well received during the datathon with 160 participants and 15,000 requests executed with a maximum duration of one minute.

Conclusions:

The resulting MIMIC-OMOP dataset is the first MIMIC-OMOP dataset available free of charge with real disidentified data ready for replicable intensive care research. This approach can be generalized to any medical field.